Online human walking imitation in task and joint space based on quadratic programming

Kai Hu, Christian Ott, Dongheui Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

25 Scopus citations

Abstract

This paper presents an online methodology for imitating human walking motion of a humanoid robot in task and joint space simultaneously. Two aspects are essential for a successful walking imitation: stable footprints represented in task space and motion similarity represented in joint space. The human footprints are recognized from the captured motion data and imitated by the robot through conventional zero-moment point (ZMP) control scheme. Additionally we focus on similar knee joint trajectories for the motion similarity, which are related to knee stretching and swing leg motion. The inverse kinematics suffers from three problems: knee singularity, strongly conflicting tasks and underactuation. We formulate this problem as a quadratic programming (QP) with dynamic equality and inequality constraints. The discontinuity of dynamic task switching is solved by introducing an activation buffer, resulting in a cascaded QP form. Finally we evaluate the effectiveness of the proposed approach on the DLR humanoid robot TORO.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3458-3464
Number of pages7
ISBN (Electronic)9781479936854, 9781479936854
DOIs
StatePublished - 22 Sep 2014
Externally publishedYes
Event2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China
Duration: 31 May 20147 Jun 2014

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2014 IEEE International Conference on Robotics and Automation, ICRA 2014
Country/TerritoryChina
CityHong Kong
Period31/05/147/06/14

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